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Why variance is bigger than standard deviation?
The variance is standard deviation squared, or, in other terms, the standard deviation is the square root of the variance. In many cases, this means that the variance is bigger than the standard deviation - but not always, it depends on the specific values.
What is the normal distribution for clothing sizes?
You can find regulations about clothing sizes in the EN 13402 standard, and a series of physical measurements in the SIRI-dataset. Reading the standard, I see that t-shirt sizes (men), for example, are mainly based on chest circumferences. Size 'M' is suitable for chest circumferences between 94 and 102 cm. Size S is 8 cm smaller, size L is 8 cm bigger, XL is 16 cm bigger and XS is 16 cm smaller than size M. When I calculate the median and standard deviation of all the chest circumferences (adult males) I find in the SIRI-dataset, I find a median of 99.6 cm, and - surprise - a standard deviation of 8.4 cm. So, I tend to believe that clothing sizes follow, in some way, the normal distribution. Size M refers to the median size, and the intervals between the size codes have about the same value as the standard deviation. So, size S is one standard deviation smaller than size M, and XL is two standard deviations bigger than size M. If haven't checked other types of clothes and other physical sizes, so I cannot guarantee that my conclusion is correct for any type of garment.
How many town lot in an acre?
A town lot is not a standard measure!A town lot is not a standard measure of area. So some town lots are bigger than others and therefore there will be fewer such lots in an acre.
What is bigger 5.8 or 5.08?
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What is the definition for skew in math terms?
The skewness of a random variable X is the third standardised moment of the distribution. If the mean of the distribution is m and the standard deviation is s, then the skewness, g1 = E[{(X - m)/s}3] where E is the expected value. Skewness is a measure of the degree to which data tend to be on one side of the mean or the other. A skewness of zero indicates symmetry. Positive skewness indicates there are more values that are below the mean but the the ones that are above the mean, although fewer, are substantially bigger. Negative skewness is defined analogously.
